Data Engineer II

Role overview

We are looking for a Data Engineer II to join the Trips Data Marketing area and help build reliable, scalable data products that enable better decision-making across the Connected Trip. This role sits at the intersection of data engineering, data modelling, governance, and stakeholder delivery, with a strong focus on improving trusted data availability, standardisation, and operational efficiency for marketing and cross-functional teams.

You will design and build data pipelines, scalable data models, and quality controls that make marketing and Trips data easier to access, trust, and use. The team's broader mission includes enabling compliant and standardised data, embedding privacy and governance by design, and reducing manual fragmentation in how data is delivered to consumers.

As a Data Engineer II, you will independently own technical deliverables, contribute to the design of reusable data solutions, and collaborate across teams to improve the reliability, consistency, and usability of our data products.

• Design, build, and maintain batch and/or streaming data pipelines that power Trips data products for marketing and adjacent business domains.

• Design and implement scalable conceptual, logical, and physical data models that support reporting, analytics, stakeholder self-service, and operational decision-making, ensuring consistency, reusability, and maintainability.

• Improve the reliability, observability, and quality of data assets through monitoring, testing, validation, and incident resolution.

• Partner with product managers, analysts, FP&A, marketers, and engineering teams to translate business requirements into scalable technical solutions and robust data models.

• Standardise data definitions, schemas, and delivery mechanisms across teams to improve consistency and reduce duplication.

• Support governance and privacy-by-design practices by embedding data quality controls, documentation, metadata, and compliance-minded ways of working throughout the data lifecycle.

• Improve developer and stakeholder experience by simplifying workflows, strengthening documentation, and promoting reusable data engineering patterns across teams.

• Optimize data pipelines and data models for performance, scalability, cost efficiency, and maintainability.

• Contribute to technical discussions, solution design, delivery planning, and cross-team collaboration for shared Trips Data initiatives.

• Support operational excellence by participating in incident resolution, root cause analysis, and continuous improvement of data pipeline reliability.

• Data pipelines and assets are dependable, well-monitored, scalable, and easy to maintain.

• Scalable, well-governed data models enable consistent reporting and analytics across teams while reducing duplication and improving data reuse.

• Stakeholders have faster access to trusted, standardised datasets for decision-making.

• Manual handoffs and fragmented delivery processes are reduced through reusable data products and standardized practices.

• Data quality issues are surfaced early and resolved systematically through testing, monitoring, and observability.

• Governance, privacy, and operational standards are embedded into delivery from the outset.

• Data products are adopted by multiple teams and contribute to improved business outcomes and operational efficiency.

• Solid 5+ experience in data engineering, analytics engineering, or software engineering with a strong data focus.

• Proficiency in SQL and at least one general-purpose programming language such as Python, Java, or Scala.

• Hands-on experience building and operating production-grade batch and/or streaming data pipelines.

• Strong understanding of dimensional and analytical data modelling principles, including designing conceptual, logical, and physical data models.

• Experience designing and evolving data models that balance business requirements with scalability, performance, maintainability, and data consistency.

• Experience implementing data quality, testing, validation, and observability practices in production environments.

• Experience working with cloud data warehouses (such as Snowflake, BigQuery, or Amazon Redshift), orchestration tools (such as Airflow), and modern data processing frameworks.

• Ability to work effectively with both technical and non-technical stakeholders and translate ambiguous business requirements into practical, scalable solutions.

• Strong ownership mindset with the ability to balance delivery speed, engineering quality, and long-term maintainability.

• Clear communication skills and comfort collaborating across cross-functional, geographically distributed teams.

• Experience working in marketing, growth, commercial, or product analytics domains.

• Familiarity with data governance, metadata management, stewardship, or producer-consumer data contracts.

• Exposure to privacy, compliance, or regulated data handling requirements.

• Experience supporting self-service analytics and stakeholder-facing data products.

• Knowledge of experimentation, attribution, ROI measurement, or performance marketing data concepts.

• Experience with modern data transformation frameworks such as dbt or similar ELT tools.

• Familiarity with CI/CD practices and automated testing for data pipelines.

Trips Data is working to provide trusted, compliant, and standardised data for key marketing and Connected Trip use cases while improving the operating model through reusable data products, stronger stewardship, and scalable engineering practices. In parallel, the marketing data strategy emphasizes better data foundations, reduced manual fragmentation, and high-quality data products that enable informed investment and performance decisions.

As a Data Engineer II, you will help turn these goals into reliable, scalable data solutions by building robust pipelines, designing reusable data models, and delivering trusted datasets that teams across Booking Holdings rely on every day. Your work will improve the consistency, quality, and accessibility of marketing and Trips data, enabling faster, more confident decision-making across the business.

If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.